By Hugh F. Durrant-Whyte
Overview contemporary years have obvious an expanding curiosity within the improvement of multi-sensory robotic platforms. the cause of this curiosity stems from a awareness that there are primary barriers at the reconstruction of surroundings descriptions utilizing just a unmarried resource of sensor info. If robotic structures are ever to accomplish a level of intelligence and autonomy, they have to be capable to utilizing many various assets of sensory info in an energetic and dynamic demeanour. The observations made via different sensors of a multi-sensor approach are regularly doubtful, frequently partial, sometimes spuri9us or mistaken and sometimes geographically or geometrically imcomparable with different sensor perspectives. The sensors of those platforms are characterised by means of the variety of knowledge that they could supply and through the complexity in their operation. it's the target of a multi sensor approach to mix details from some of these various resources right into a powerful and constant description of the environment.
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Additional resources for Integration, Coordination and Control of Multi-Sensor Robot Systems
The reason for this is that the relations between features can be used to provide constraints on possible descriptions. These constraints can be interpreted as information and used, whenever feature descriptions are changed, to apply corresponding changes to related features. The simplest case of an invariant relation occurs in the loop created by the relations between three geometric objects. In this instance, the vector sum of the relations between objects is zero, regardless of the absolute location of these objects.
Consider again the example of three surfaces forming three edges and a corner. Suppose we initially have an estimate of the object parameters with some measure of uncertainty, and suppose we now make a new observation of an edge; ei. Combining prior and observed estimates of the edge parameters results in some new estimate e~. To maintain geometric consistency of the object, this new information must be propagated through the constraining relations to provide new consistent estimates for the other edges of the object.
This excludes homogeneous tensor representations or any other parameterization in which the parameter vector is of greater degree than the geometric variety that it describes. 32 MULTI-SENSOR INTEGRATION 3. The parameter vector must change "smoothly" with physical feature motion. This ensures that small changes in feature do not result in abrupt changes in the describing parameter. Conditions 1 and 2 require a representation to be a one-to-one (bijective) relation between feature and parameter.